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In the article, the error variance estimator σ ^ 2 and its finite sample size bounds are investigated in the framework of a general linear model under linear restrictions (gLMLR) where no distributions are assumed except for some moment conditions and the covariance matrix of the response may be singular, which extends the results in Lindholm and Wahl (2020). In particular, we overcome the difficulty that the matrix of quadratic form in σ ^ 2 is not idempotent. The estimator is obtained by the proposed restricted and proxy-type generalized least square procedure. Meanwhile, the estimable function of the regression coefficient β is estimated, too. Besides, the finite sample properties of these estimators and their consistency are also established. In the end, a simulation study and a real data analysis are done to examine the finite performance of these estimators. [ABSTRACT FROM AUTHOR]

Background: Procalcitonin (PCT) is a useful biomarker for infection and especially useful for sepsis management. Multiple platforms, including the chemiluminescence immunoassay (CLIA), have been used for serum PCT analysis. However, the results from different analytical platforms should be evaluated to determine if they can be mutually substituted in the same laboratory. Methods: The serum PCT were analyzed on the Mindray CL-6000i chemiluminescent immunoassay (candidate method), the Roche Elecsys, and the VIDAS PCT chemiluminescence immunoassay platforms (comparative measurements), and the results were evaluated and compared, following the CLSI EP09-A3 guidelines, by using patient samples with different PCT concentrations. Results: The median of difference was 0.04 (95% CI: 0.038 - 0.045) between the candidate method and the comparative measurements for the concentration interval of < 0.5 ng/mL. The median of percentage difference was 6.6% (95% CI: 5.5% - 8.7%) for the concentration interval of 0.5 - 2.0 ng/mL, the median of difference was 0.11 (95% CI: 0.06 - 0.17) for the concentration interval of 2.0 - 10.0 ng/mL, and the median of percentage difference was -4.7% (95% CI: -6.1% - 2.4%) for the concentration interval of 10.0 - 100.0 ng/mL. The acceptable bias was ± 0.055 (± 10.4%) at 0.53 ng/mL (low value), and the acceptable bias was ± 0.83 (± 9.0%) at 9.34 ng/mL (high value). The bias between the candidate method and comparative measurements was acceptable for the full concentration ranges. Conclusions: The bias between the PCT results from Mindray, Roche, and VIDAS was acceptable. Therefore, the results of the three analytical platforms were comparable, and they may be mixed-used in the same institution. [ABSTRACT FROM AUTHOR]

Rank regression plays a fundamental role in statistical data analysis due to its robustness and high efficiency, and has been widely used in various scientific fields. However, when the data size is huge or massive, but the computing resource is limited, it can lead to an unacceptably computational cost for rank regression estimation. To handle this issue, this paper applies a random perturbation subsampling method to rank regression models. Specifically, we develop two repeatedly random perturbation subsampling algorithms to find the estimation of parameters. Two different weighting strategies with product weights and additive weights are examined in the objective function. Differing from the existing optimal and Poisson subsampling methods, our methods do not require the explicit calculation of subsampling probabilities for all data points, in which some unknown parameters often need to be estimated, thus making the implementation of our methods easier. Theoretically, statistical justifications are further provided for the proposed estimators including consistency and asymptotic normality. Extensive simulation studies and an empirical application are carried out to illustrate the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

Purpose: Individual-level state-transition microsimulations (iSTMs) have proliferated for economic evaluations in place of cohort state transition models (cSTMs). Probabilistic economic evaluations quantify decision uncertainty and value of information (VOI). Previous studies show that iSTMs provide unbiased estimates of expected incremental net monetary benefits (EINMB), but statistical properties of iSTM-produced estimates of decision uncertainty and VOI remain uncharacterized. Methods: We compare iSTM-produced estimates of decision uncertainty and VOI to corresponding cSTMs. For a 2-alternative decision and normally distributed incremental costs and benefits, we derive analytical expressions for the probability of being cost-effective and the expected value of perfect information (EVPI) for cSTMs and iSTMs, accounting for correlations in incremental outcomes at the population and individual levels. We use numerical simulations to illustrate our findings and explore the impact of relaxing normality assumptions or having >2 decision alternatives. Results: iSTM estimates of decision uncertainty and VOI are biased but asymptotically consistent (i.e., bias approaches 0 as number of microsimulated individuals approaches infinity). Decision uncertainty depends on 1 tail of the INMB distribution (e.g., P[INMB <0]), which depends on estimated variance (larger with iSTMs given first-order noise). While iSTMs overestimate EVPI, their direction of bias for the probability of being cost-effective is ambiguous. Bias is larger when uncertainties in incremental costs and effects are negatively correlated since this increases INMB variance. Conclusions: iSTMs are useful for probabilistic economic evaluations. While more samples at the population uncertainty level are interchangeable with more microsimulations for estimating EINMB, minimizing iSTM bias in estimating decision uncertainty and VOI depends on sufficient microsimulations. Analysts should account for this when allocating their computational budgets and, at minimum, characterize such bias in their reported results. Highlights: Individual-level state-transition microsimulation models (iSTMs) produce biased but consistent estimates of the probability that interventions are cost-effective. iSTMs also produce biased but consistent estimates of the expected value of perfect information. The biases in these decision uncertainty and value-of-information measures are not reduced by more parameter sets being sampled from their population-level uncertainty distribution but rather by more individuals being microsimulated for each parameter set sampled. Analysts using iSTMs to quantify decision uncertainty and value of information should account for these biases when allocating their computational budgets and, at minimum, characterize such bias in their reported results. [ABSTRACT FROM AUTHOR]

The Bradley-Terry model is a common model for analyzing paired comparison data. Under differential private mechanism, there is a lack of asymptotic properties for the parameter estimator of parameters in this model. In this article, we show that the moment estimators of the parameters based on the differential private degree sequence with Laplace noise is uniformly consistent and asymptotically normal. Simulations are provided to illustrate asymptotic results. [ABSTRACT FROM AUTHOR]

The analysis of continuous events for any application involves the discretization of an event into sequences with potential historical dependencies. These sequences represent time stamps or samplings of a continuous process collectively forming a time series dataset utilized for training recurrent neural networks (RNNs) such as Long Short-Term Memory (LSTM) and Gated Recurrent Unit (GRU) for pattern prediction. The challenge is to ensure that the estimates from the trained models are consistent in the same input domain for different discretizations of the same or similar continuous history-dependent events. In other words, if different time stamps are used during the prediction phase after training, the model is still expected to give consistent predictions based on the knowledge it has learned. To address this, we present a novel RNN transition formula intended to produce consistent estimates in a wide range of engineering applications. The approach was validated with synthetically generated datasets in 1D, 2D, and 3D spaces, intentionally designed to exhibit high non-linearity and complexity. Furthermore, we have verified our results with real-world datasets to ensure practical applicability and robustness. These assessments show the ability of the proposed method, which involves restructuring the mathematical structure and extending conventional RNN architectures, to provide reliable and consistent estimates for complex time series data. [ABSTRACT FROM AUTHOR]

AbstractIn the field of neuropsychology, the accuracy of neuropsychological data interpretation has significant implications for both research and clinical practice. The process of test interpretation is fraught with challenges, and a lack of consensus among neuropsychologists can lead to discrepancies in assessment outcomes. Smith et al. (2020) identified this concerning lack of consensus in test score interpretation, raising questions about the standardization of interpretive practices within the field. Similarly, Tuokko and Gabriel (2006) reported moderate interrater agreement in identifying cognitive impairments, with a 77.7% consensus rate, using both history and all available information. The current study investigated the extent to which independent neuropsychologists could reach consistent diagnostic conclusions using only numeric data and the statistical methods available in the Meyers Neuropsychological Battery (MNB), without access to clinical history or contextual information. The results demonstrated a high degree of accuracy, with an overall agreement rate of 85.5% to 92.2% among the six raters. This finding underscores the potential of standardized statistical approaches to enhance the objectivity and consistency of neuropsychological assessments. The study advances neuropsychological assessment methodology by showing that statistical pattern-matching techniques can yield reliable and uniform diagnostic outcomes, even in the absence of additional clinical data. [ABSTRACT FROM AUTHOR]

The Asymmetric Information Management (AIM) technique encourages truth tellers to adopt a forthcoming verbal strategy and liars a withholding strategy. We investigated the effectiveness of this technique using a follow-up statement. We predicted that truth tellers in the AIM condition would provide more new and overall detail, with a higher proportion of complications, compared to control truth tellers, whereas AIM liars would use more self-handicapping strategies and common knowledge details, with fewer commissions, repetitions, and less overall detail than control liars. This was tested using a mixed-factors design in which truth tellers (n = 65) gave an honest recollection of a recent trip while liars fabricated a story (n = 62). Participants provided an initial statement and half received the AIM instructions prior to providing their second statement. Truth tellers in the AIM condition provided more new detail and complications in their second statement compared to truth telling controls. Unlike previous research, AIM instructions had no significant effect on liars' statements. No other differences emerged. In conclusion, the AIM instructions elicit some new information from truth tellers but do not improve classification from liars. [ABSTRACT FROM AUTHOR]

If computers or robots were to replace human scientists, should they adhere to our established principles of the Philosophy of Science? We have been taught to value consistency, Popperian falsifiability, and Occam's razor (also known as the principle of parsimony). While these traditional philosophical principles are valuable, they might limit the exploration of complex phenomena that require more nuanced or multifaceted approaches. Specific formal contexts exist where these principles falter when confronted with reality, as traditional scientific methods may reduce cognitive power. This paper formally highlights the limitations of traditional scientific and philosophical principles through the mathematics of computability (which will be considered softly). [ABSTRACT FROM AUTHOR]

There is evidence that mastery motivation contributes to developmental outcomes, both for typically developing individuals and for those with disabilities such as Down syndrome. Mastery motivation appears to be a stable trait, at least during early childhood, but research with adults has been restricted by the absence of an appropriate measure. The current study investigated the stability and consistency of parent-reported mastery motivation for 21 individuals with Down syndrome across 20 years. Parents completed the Dimensions of Mastery Motivation Questionnaire (DMQ) when their child was aged 4–6 years and 11–15 years. They completed the Dimensions of Adult Mastery Motivation Questionnaire (DAMMQ) when their son or daughter was 23–27 years old. There were strong positive correlations among measures of mastery motivation across the three time points. Persistence decreased significantly from early childhood to adolescence but increased from adolescence to adulthood. Most individual profiles fitted this pattern, with only one of the 21 participants showing continual declines in persistence. For individuals with Down syndrome, patterns of mastery motivation may be developed early in life and sustained into adulthood. [ABSTRACT FROM AUTHOR]

Performance of sport-related ballistic motor skills, like ball hitting in golf and baseball, requires wide movements to produce highly fast and spatially accurate movements. In this study, we assessed the effect of movement amplitude on directional accuracy in a ballistic hitting task. Participants performed the task of moving a manual handle over a flat surface to hit with high speed a moveable disc, aiming to propel it towards a frontal target. Five movement amplitudes were compared, ranging from 11.5 cm to 27.5 cm in steps of 4 cm. Kinematic analysis evaluated motions of the handle, disc, and arm joints. Results showed that greater movement amplitudes led to longer acceleration phases, with delayed peak velocities at the handle, shoulder and elbow, leading to higher contact and peak linear velocities of the handle, and higher angular velocities at the shoulder and elbow. Manipulation of movement amplitude led to no evidence for effects on either disc directional accuracy or variability. Results also revealed no evidence for differences in variability of contact velocity, peak velocity and time of peak velocity across movement amplitudes in the shoulder, elbow, and wrist. Our results indicated that greater movement amplitudes in hitting a spatial target lead to increased contact velocity while not affecting directional accuracy or movement variability. [ABSTRACT FROM AUTHOR]

The agreement between a wearable inertial sensor (GYKO, G) and the force platform (P) was assessed by evaluating test-retest and inter-rater reliability. Thirty-eight subjects were enrolled; the selected indices of balance were investigated over foot positions and (un)stable conditions. Intraclass correlation coefficient (ICC), standard error of measurement (SEM%) and minimal detectable change (MDC95%) were computed. For G, ICC bounds range from poor to excellent (0.040 ÷ 0.921), mean of 0.687 (= moderate reliability). Regarding P, ICC ranges from poor to excellent (0.070 ÷ 0.920), mean of 0.683 (= moderate reliability). For G, SEM% ranges from 11% to 47%; MDC95% from 30% to 132%. Concerning P, SEM% ranges from 7% to 41%; MDC95% from 21% to 114%. Finally, the inter-rater reliability ICC by comparing devices ranges from poor to excellent (−0.162 ÷ 0.911), mean of 0.338 (= poor reliability). GYKO appears to be a convenient tool with high consistency among multiple measurements but for specific clinic/research purposes. [ABSTRACT FROM AUTHOR]

Copyright of Journal of China Medical University is the property of Journal of China Medical University Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

As an extension of linear regression in functional data analysis, functional linear regression has been studied by many researchers and applied in various fields. However, in many cases, data is collected sequentially over time, for example the financial series, so it is necessary to consider the autocorrelated structure of errors in functional regression background. To this end, this paper considers a multiple functional linear model with autoregressive errors. Based on the functional principal component analysis, we apply the least square procedure to estimate the functional coefficients and autoregression coefficients. Under some regular conditions, we establish the asymptotic properties of the proposed estimators. A simulation study is conducted to investigate the finite sample performance of our estimators. A real example on China's weather data is applied to illustrate the validity of our model. [ABSTRACT FROM AUTHOR]

This paper presents an efficient numerical approach for first-order delay differential equations containing a piece-wise constant delay. The strategy is based on a five-point hybrid block method that has been developed for ordinary differential equations. We will use the interpolation technique for the evaluation of delay terms that are not defined at the grid points. The main characteristics are discussed, including zero stability, local truncation errors, convergence and stability region. The method is easy to implement, and the numerical experiments show the efficiency and accuracy of the proposed method, compared to other methods appeared in the literature. [ABSTRACT FROM AUTHOR]

The rapid growth in the storage scale of wide-area distributed file systems (DFS) calls for fast and scalable metadata management. Metadata replication is the widely used technique for improving the performance and scalability of metadata management. Because of the POSIX requirement of file systems, many existing metadata management techniques utilize a costly design for the sake of metadata consistency, leading to unacceptable performance overhead. We propose a new metadata consistency maintenance method (ICCG), which includes an incremental consistency guaranteed directory tree synchronization (ICGDT) and a causal consistency guaranteed replica index synchronization (CCGRI), to ensure system performance without sacrificing metadata consistency. ICGDT uses a flexible consistency scheme based on the state of files and directories maintained through the conflict state tree to provide an incremental consistency for metadata, which satisfies both metadata consistency and performance requirements. CCGRI ensures low latency and consistent access to data by establishing a causal consistency for replica indexes through multi-version extent trees and logical time. Experimental results demonstrate the effectiveness of our methods. Compared with the strong consistency policies widely used in modern DFSes, our methods significantly improve the system performance. For example, in file creation, ICCG can improve the performance of directory tree operations by at least 36.4 times. [ABSTRACT FROM AUTHOR]

Incorporating corporate social responsibility (CSR) into organizational strategies has become essential, demonstrating a dedication to ethical conduct and sustainable practices. This paper investigates how consistency in CSR practices impacts organizational attractiveness. Drawing upon the theory of the continuum model of impression formation, two separate studies were undertaken to investigate the influence of CSR consistency (both consistent and inconsistent CSR) on the appeal of organizations. Besides, these studies aimed to evaluate the mediating roles of conceptual fluency and perceived corporate hypocrisy in this relationship, as well as the moderating effect of two corporate communication strategies (proactive and passive). The study found that perceptions of corporate hypocrisy played a significant mediating role in the link between inconsistent CSR practices and the appeal of an organization. This mediating effect was diminished by the use of proactive communication strategies. In contrast, conceptual fluency was identified as a key mediator in the relationship between consistent CSR practices and organizational attractiveness, with its mediating effect being enhanced by proactive communication strategies. This study makes a novel contribution by focusing on the temporal stability of CSR initiatives and broadens the understanding of whether sustained engagement in CSR activities over time confers greater organizational attractiveness than occasional or random initiatives. This study extends the theory of the relationship between perceived CSR and job seekers and provides guidance and recommendations for CSR activities and HR recruitment practices for companies in the post‐epidemic era. [ABSTRACT FROM AUTHOR]

Copyright of Arabic Language & Literature (1735-9767) is the property of University of Tehran and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Larq Journal for Philosophy, Linguistics & Social Sciences is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Background: During tumor progression, HER2 expression undergoes dynamic changes. Circulating tumor cells (CTCs) can be used to monitor HER2 expression in real-time and hold potential for clinical application. This study aimed to evaluate the consistency of HER2 expression between primary tumors and CTCs in patients with breast cancer (BC). Methods: We used a previously established telomerase reverse transcriptase-based CTC detection method (TBCD) combined with anti-HER2 antibody to detect CTC and HER2-positive CTC (HER2 + CTC) in 4 ml of peripheral blood from patients with breast cancer prior to radiotherapy. The results indicated that the status of HER2 in CTC was inconsistent with the histological results. Results: Discordance in HER2 status between primary tumor and CTC was observed in 32.6% of patients (kappa value = 0.325, p = 0.03). And among patients with histologically HER2-negative breast cancer, the detection rate of HER2 + CTC was 32.1% (9/28). Conclusions: We found that the HER2 status of CTC in peripheral blood was inconsistent with the histological findings. Further research should explore the clinical significance of detecting HER2-positive CTCs, and it is desired that real-time HER2 status testing of CTCs could hold potential value for patients with breast cancer. [ABSTRACT FROM AUTHOR]

In this article, a new method is introduced under the Bayesian framework to derive the credibility estimator of risk premiums based on the Esscher premium principle. This new estimator offers desirable statistical properties, making it more useful and practical compared to existing estimators. Additionally, Bayesian models for policy portfolios are established, and empirical Bayes methods are employed to estimate the structural parameters. The empirical Bayesian estimation of risk premiums is also discussed in detail. The convergence rate and goodness of the proposed estimators are verified through simulations. The results demonstrate the effectiveness and accuracy of the new estimator and its superior performance compared to other existing methods. Finally, an empirical analysis is conducted using real insurance data, which further confirms the applicability and reliability of the proposed credibility estimator and its superiority in practical insurance applications. [ABSTRACT FROM AUTHOR]

Let $ \{X_{i},1\leq i\leq n\} $ { X i , 1 ≤ i ≤ n } be a sequence of linear process based on dependent random variables with random coefficients, which has a mean shift at an unknown location. The weighted sum of powers in mean (WSPM, for short) estimator of the change point is proposed. The weak consistency, the rate of weak consistency and strong consistency for the WSPM estimator are established under some mild conditions. Simulation studies and two real data exercises are also provided to show the superiority of this new method to some existing methods. [ABSTRACT FROM AUTHOR]

Countermovement jump (CMJ) performance analysis is vital in sports science for assessing lower-body strength and neuromuscular efficiency. This study evaluated the validity of the Enode Sensor and My Jump 3 App for measuring vertical jump heights, comparing them to those measured using the established Force Plate. Twenty-nine participants performed CMJs measured using each device. Descriptive statistics indicated mean jump heights of 48.4 ± 4.18 cm (for the Enode Sensor), 47.3 ± 4.05 cm (for My Jump 3), and 46.1 ± 4.03 cm (for the Force Plate). Reliability was confirmed via Intraclass Correlation Coefficients (ICCs), with the Enode Sensor at 0.914 and My Jump 3 at 0.968, demonstrating excellent reliability. Bland–Altman analysis showed mean biases of 2.281 cm (for the Enode Sensor) and 1.297 cm (for My Jump 3) against the Force Plate, with limits of agreement suggesting close alignment. Strong positive correlations were observed (for the Enode Sensor, r = 0.972 and for My Jump 3, r = 0.987; p < 0.001), and linear regression analysis produced R2 values of 0.945 and 0.973, respectively, confirming both tools' accuracy for vertical jump measurement. These findings indicate that although both tools are suitable for CMJ assessment, My Jump 3 demonstrated slightly superior accuracy, underscoring the potential for accessible, reliable performance monitoring in sports contexts. [ABSTRACT FROM AUTHOR]

Translation abstract Project‐accompanying strategies for sustainable material selectionThe construction sector is Germany's most resource‐intensive economic sector, despite significant progress in building operation efficiency. However, efficiency gains are often offset by rebound effects in building usage. Construction methods and materials are becoming increasingly important in energy‐efficient buildings during operation. Sustainability strategies such as sufficiency and consistency often remain overlooked. The DGNB certification system supports the equitable implementation of sustainability strategies but requires a clear understanding of tasks and defined responsibilities. Central criteria include resource efficiency, circularity, and freedom from pollutants. Measures such as the use of bio‐based or recycled construction materials and the ability to deconstruct buildings reduce environmental impacts and lifecycle costs. Digital tools and building resource passports enhance transparency and reusability. The DGNB system recognizes that sufficiency and consistency are key principles of sustainable construction. A team‐oriented approach supported by digital tools facilitates the integration of sustainability aspects and maximizes their potential. [ABSTRACT FROM AUTHOR]

Background: Quality data is crucial in making informed decisions regarding health services; However, the literature suggests that in many LMICs including Malawi, it remains of poor quality. Data quality is measured in terms of completeness, timeliness and consistency among other parameters. We describe the Ministry of Health's District Health Information System (DHIS2) report completeness and timeliness at three levels: National, South West Zone (SWZ) and Neno district. Further, describe data consistency following data quality assessments (DQA) in Neno district, Malawi. Methods: We conducted a descriptive retrospective study by extracting DHIS2 report completeness and timeliness at three levels and used DQA data in Neno district between January 2016 and December 2022. We defined report completeness as the number of reports in DHIS2 against those expected, timeliness as the number of reports entered into DHIS2 before the deadline and consistency as the level of agreement between three sources: register, report and DHIS2 system. We presented the data graphically and calculated yearly median reporting rates for weekly, monthly and quarterly reports against the national target of 85%. We utilized a verification factor (VF) of 0–200% to evaluate consistency between three sources in the Neno district. VF exceeding 100% indicated over-reporting, 100% as a perfect match, and less than 100% as under-reporting, with an acceptable 90–110% range. Results: During the study period, we found increased trends in weekly, monthly and quarterly report completeness at all three levels but were below 85%. Neno district surpassed the target from 2020 onward for weekly reports and from 2019 onward for monthly reports. Similar increased trends were observed for report timeliness with below threshold of 85% except for Neno district monthly report from 2021 onward. We found inconsistencies in data entry from the report to DHIS2 (VF: >90% - <110%) in Neno district. Similarly, under and over-reporting occurred between the register and the report (VF: <90% and > 110%) were observed. These findings should be considered when using DHIS2 for decision-making. Conclusion: In general, we found increased completeness and timeliness rates at all three levels, however, less than the set target of 85%. We suggest continued support, including routine DQAs and report monitoring, towards improving DHIS2 data quality. [ABSTRACT FROM AUTHOR]

The task of coordinating expert assessments inevitably arises in the expert construction of integral indicators of objective judging in sports, analysis of the state and risks of functioning of social, economic, environmental, transportation systems and for many other subject areas of human activity. A decision-maker, as a rule, sets a criterion by which an object is evaluated, and an expert defines a set of comparable objects according to this criterion and evaluates each object, ranking them in descending (ascending) order of one or another quality. It is assumed that the expert has his own opinion that does not diverge from the generally accepted one and is not built only on the basis of measurable data. This opinion is based on his/her personal experience and knowledge gained in the process of work. As a result, there is often a situation when the transitivity of expert evaluations is violated. The proposed procedures for finding an integral indicator can be used in the tasks of decision-making, harmonization of expert assessments of the state of objects, construction of environmental and social indicators, as well as quality indicators, such as the integral indicator of the quality of life, the index of the quality of the transport system, the index of human development, etc. The methods of matrix theory are applied. The methods of matrix theory, graph theory and combinatorics are applied. The presented algorithm differs from existing methods in that it measures the contribution of the total error of experts to the collective measure of their consistency. The method under discussion offers a solution for decision makers in the so-called group selection problem (which means the task of analyzing and aggregating heterogeneous information about the preferences of compared objects into a single "group" preference) of critical objects that require increased attention of the security service and expenditure of resources of the state and the owner of the system to ensure their safety, security and sustainability of operation. [ABSTRACT FROM AUTHOR]

Owing to the superior stimulus perception, tactile function of skin is always the desire of flexible pressure sensor array (FPSA). However, achieving sensor arrays with high sensitivity and high resolution for tactile recognition like skin still remains a challenge. In this paper, an FPSA with high sensitivity (10.50 kPa−1), high density (1134.63 cm−2), and sufficient sensing units (4096 units) is developed, which is one of the best results up to now. The spinous microstructures, transferring from the abrasive papers, endow the sensor array with high sensitivity. Additionally, the high density array with adequate sensing units contributes to achieving high spatial resolution for identifying various surface features. This high‐performance FPSA can obtain detailed pressure distribution for complex carved patterns. With the assistance of machine learning, the FPSA can realize precise tactile recognition, 98.48% accuracy for 12 types of mahjong tiles, indicating a promising potential in an intelligent recognition system. It is worth noting that the relationship between surface microstructures and consistency is systematically investigated for the first time, which offers valuable insights for the preparation of high‐performance sensor arrays. [ABSTRACT FROM AUTHOR]

Key digested message Reliability is crucial in psychometric testing, as it helps obtain consistent and accurate measurements. The British Psychological Society's independent review process assesses reliability across multiple facets that include internal consistency, split-half reliability, and test-retest reliability. Incorporating highly reliable psychometrics into research increases the likelihood of obtaining findings that future studies can replicate, thereby increasing the credibility of their insights when applied to various professional settings. [ABSTRACT FROM AUTHOR]

This paper offers an initial evaluation of the organizational and structural relationships among reliability and best warranty programme. In the producing sectors because of automation, plant potential has been extended with inside the system industries. This enables in growing productiveness in addition to the best of the material, but every computerized industry, massive funding remains the top anxiety. Consequently, it additionally anticipated the running structures ought to work for a long time and defective-free. In the time being, it turns into essential to present right care of running machines. Operation of those features and using precise strategies in those regions and the obstacles to their reputation has additionally been discussed. The contemporary paper offers the evaluation of the consistency evaluation. Consistency evaluation of numerous structures is evaluated in specific system productions just like the sugar production, updraft energy productions, milk productions, mining, petroleum productions, etc. The series of reliability and best expenses records and its use with the aid of using pinnacle control in decision-making regarding destiny upgrades have additionally been covered. The specific tactics are used by investigators in numerous grounds to test the overall activity of the running machine. These tactics are genomic procedure, fault tree evaluation, deficiency and impact evaluation, petrify-nets, dependability, accessibility, maintainability and deprivation modeling strategies etc. The growth has been shown from the overall performance of the structures mainly totally depend upon numerous records through the above tactics. [ABSTRACT FROM AUTHOR]

This paper proposes a multivariate form of generalized information criterion (MGIC) for the multivariate response bridge regression (multi-bridge) model. Also, we prove the identifiability of the multi-bridge as a prerequisite for model selection. We introduce the general form of MGIC for regularization parameter selection in the multi-bridge model. We assess the performance of MGIC variants from three viewpoints: consistency of the obtained models, analysis of high-dimensional data, and comparison to other criteria. Based on the numerical study, we reach better performance for MGIC in comparison to other common criteria (cross-validation and GCV) using simulated and real datasets. [ABSTRACT FROM AUTHOR]

Currently, automotive manufacturers highly prioritize the perceived quality of vehicles, with dimensional engineering being a key influencing factor. Automotive interior and exterior trim components undergo slight deformation due to temperature changes, affecting fit dimensions and imposing stricter consistency requirements. This paper examines the deformation mechanisms of typical parts under varying temperatures using dimensional engineering techniques to study the impact on component gaps. Testing quantifies changes in gap width and surface flatness during temperature variations, providing a theoretical basis for design. The research offers practical guidance for identifying potential issues early in product development and ensuring effective collaboration in production, helping companies achieve higher standards and superior quality. [ABSTRACT FROM AUTHOR]

In this paper I investigate whether there are any cases in which it is rational for a person to hold inconsistent beliefs and, if there are, just what implications this might have for the theory of epistemic justification. A number of issues will crop up along the way – including the relation between justification and rationality, the nature of defeat, the possibility of epistemic dilemmas, the importance of positive epistemic duties, and the distinction between transitional and terminal attitudes. [ABSTRACT FROM AUTHOR]

The study aimed to analyse serum haptoglobin concentrations by calving number and lactation phase in clinically healthy dairy cattle and to determine the correlation between concentrations in serum and milk samples. For this purpose, serum samples were collected from 228 clinically healthy cows after milking from 14 randomly selected herds. Additionally, milk samples were collected from 80 out of the 228 cows from the milking prior to blood collection. Both serum and milk samples were analysed with a commercial ELISA test. The effect of the calving number and lactation phase on mean serum haptoglobin concentrations was examined by Kruskal–Wallis/Jonckheere–Terpstra tests. After that, in a multivariate approach, a mixed-effects linear model was also performed. In addition, intraclass correlation coefficients were used to evaluate the correlation between concentrations in serum and milk samples. Results indicated a downward trend in haptoglobin concentrations throughout lactation, that was statistically significant when comparing fresh cows with the remaining lactation phases. The higher haptoglobin concentrations in fresh cows could be the result of inflammatory illnesses without clinical disease, stress or variations within the physiological state. Although previous studies showed some discrepancies, a good correlation between serum and milk concentrations has been observed in the present paper. [ABSTRACT FROM AUTHOR]

Land cover data are essential for modelling land surface processes in mountainous regions. Fine-resolution land cover products have provided unprecedented spatial detail of the land surface. The performance of land cover classification can be affected by various causes, propagating uncertainty through modelling. In this study, six openly accessible fine-resolution land cover data products for 2020, namely GlobeLand30, CLCD, GLC_FCS30, Esri land cover, WorldCover, and DynamicWorld, were cross-compared for consistency and accuracy in the Changbai Mountain Range. The study particularly highlighted the consistency and accuracy across various geomorphic types. The findings reveal that all the six data products exhibit an overall similarity in spatial patterns dominated by cropland and forest. Validation using a ground reference dataset revealed that WorldCover and GlobeLand30 provide the highest and lowest accuracy, respectively. Cropland and forest present considerable spatial consistencies among the data products and advanced accuracies. The middle-mountain regions with low landscape diversity and fragmentation showed the highest consistency and accuracy. Data products, however, are difficult to represent the distribution of grassland, wetland, and bare ground categories reliably due to limited consistency and accuracy. This study provides quantitative analysis for selecting appropriate land cover data products towards application implementations. [ABSTRACT FROM AUTHOR]

In this article, the complete f-moment convergence for m-asymptotic negatively associated random variables is investigated. As applications, we establish the strong consistency of the least square estimator in the simple linear errors-in-variables models and the complete consistency for estimator in the semiparametric regression model based on m-asymptotic negatively associated errors. We also give some simulations to assess the finite sample performance of the theoretical results. [ABSTRACT FROM AUTHOR]

The annual disposal of rice husk ash (RHA) and fly ash (FA) from agro-based and power plants are substantial causing pollution, land acquisition for waste disposal, diseases related to respiratory and other negative impacts. The incorporation of rice-husk ash (RHA) and Fly Ash (FA) with lime (L) as a soil additive is a recent development, and its impact on soil mechanical qualities has been thoroughly investigated in this experimental study. This in-depth experimental study aims to investigate the impact of consistency and compatibility of RHA and FA at varying rates from 10 to 20% with 5% increments on clayey soil. About 18 samples of varying proportion were prepared and subjected to experimental evaluation. The experimental procedures in soil stabilization involve combining lime and raw soil with varying percentages of FA (10%, 15%, and 20%) and RHA (10%, 15%, and 20%). With 2% lime mixed with 20% RHA & 15% FA proportion, the highest value of OMC and MBD was recorded. This also implies the application of RHA and FA reduced the maximum dry bulk density (MBD) while increasing the optimum water content (OWC). The consistency limit of this proportion was showing decreased plasticity because the soil's flocculated structure was filled with fine ash particles, filling up all the spaces. [ABSTRACT FROM AUTHOR]

The effects of class-F coal fly ash (CFA) as cement replacement in the paste and mortar formulation at different CFA-to-binder ratios (CBR) with varying water-to-binder ratios (WBR) were investigated and further evaluated using multivariate nonlinear regression to elucidate their influence on consistency, setting time, and water requirement. It was found that the required WBR for achieving normal consistency of formulated paste and mortar can be predicted using the obtained regression models. Water requirements for mortar formulation could also be predicted, given that the water requirement for paste formulation is known. The influence of partially replacing cement in mortar formulations on hardened mortar properties while ensuring formulations were at normal consistency was also investigated with replacements of up to 20 wt.% resulted in a mortar with improved strength, especially after curing for 28 and 56 days, as the CFA exhibits its inherent pozzolanic activity. [ABSTRACT FROM AUTHOR]

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The paper discusses duration effects on the consistency of mean parameter and dispersion parameter estimators in exponential dispersion families (EDFs) that are the standard models used for non-life insurance pricing. Focus is on the standard generalised linear model assumptions where both the mean and variance, conditional on duration, are linear functions in terms of duration. We derive simple convergence results that highlight consequences when the linear conditional moment assumptions are not satisfied. These results illustrate that: (i) the resulting mean estimators always have a relevant asymptotic interpretation in terms of the duration adjusted actuarially fair premium—a premium that only agrees with the standard actuarial premium using a duration equal to one, given that the expected value is linear in the duration; (ii) deviance based estimators of the dispersion parameter in an EDF should be avoided in favour of Pearson estimators; (iii) unless the linear moment assumptions are satisfied, consistency of dispersion and plug-in variance estimators can not be guaranteed and may result in spurious over-dispersion. The results provide explicit conditions on the underlying data generating process that will lead to spurious over-dispersion that can be used for model checking. This is illustrated based on real insurance data, where it is concluded that the linear moment assumptions are violated, which results in non-negligible spurious over-dispersion. [ABSTRACT FROM AUTHOR]

The pivotal role of greening production methods is indispensable in facilitating the sustainable development of China's agricultural sector and its modernization process. Translating farmers' ecological cognition into environmentally conscious production behavior constitutes a fundamental strategy for advancing the green transformation within China's agriculture. However, a recurrent issue arises from an inconsistency between farmers' green production behavior and their ecological cognition. Meanwhile, the current research has fewer studies on the consistency of farmers' cognition and behavior, and more analysis of the logical hierarchical relationship between their influencing factors needs to be done. Based on a field survey of 399 farmers in Hainan Province, this paper first employs descriptive statistics to assess the consistency of farmers' ecological cognition with their green production behavior. Second, this study uses a Logistic model and Interpretative Structural Model (ISM) to empirically analyze the factors influencing such consistency and the internal logical relationships of these factors. The results reveal that merely 28% of farmers exhibit consistency between their ecological cognition and green production practices. Secondly, education level, health status, political capital, household expenditure, planting scales, risk preference, peer influences, policy cognition, social networks, and information acquisition significantly influence this "consistency." Thirdly, the logical hierarchical relationships established via the ISM indicate that peer influences and risk preference are the surface direct factors; policy cognition, information acquisition, social networks, and planting scales are middle indirect factors; education level, political capital, health status, and household expenditure are deep-rooted factors that underpin the entire framework. Given these insights, this study recommends that the government undertake initiatives to reinforce education and training programs, enhance accessibility to information and technical support, and tailor policies to accommodate small-scale farmers. This study endeavor contributes to an enhanced comprehension of the factors influencing the transformation of farmers' ecological cognition into green production behavior, also presenting pragmatic policy proposals to advance sustainable agriculture in China. [ABSTRACT FROM AUTHOR]

Copyright of Arab Journal of Science & Research Publishing is the property of Mussasat Al-Majallah Al-Arabiyah lil-Ulum Wa-Nashr Al-Abhath and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Journal of Graphics is the property of Journal of Graphics Editorial Office and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The need for bearings in a variety of heavily loaded machines, including the influence of pressure and temperature, is generating increasing interest in studying the operating environment for magazine bearings. The purpose of this work is to develop a semi-analytical solution by introducing a new delta profile concept of the location of zero velocity gradients to obtain the simplest form of the equation of energy and Reynolds. In the journal bearing, assuming that journal is rotating and bearing is fixed, a hydrodynamic lubrication is modelled with the Power Law fluid. The lubricant temperature effect is examined under isothermal limits and the results obtained are much more realistic with the experimental results. [ABSTRACT FROM AUTHOR]

Foot-and-mouth disease (FMD) is a viral disease that affects cloven-hoofed animals including cattle, pigs, and sheep, hence causing export bans among others, causing high economic losses due to reduced productivity. The global effect of FMD is most felt where livestock rearing forms an important source of income. It is therefore important to understand the modes of transmission of FMD to control its spread and prevent its occurrence. This work intends to address these dynamics by including the efficacy of active migrant animals transporting the disease from one area to another in a fuzzy mathematical modeling framework. Historical models of epidemics are determinable with a set of deterministic parameters and this does not reflect on real-life scenarios as observed in FMD. Fuzzy theory is used in this model as it permits the inclusion of uncertainties in the model; this makes the model more of a reality regarding disease transmission. A time lag, in this case, denotes the incubation period and other time-related factors affecting the spread of FMD and, therefore, is added to the current model for FMD. To that purpose, the analysis of steady states and the basic reproduction number are performed and, in addition, the stability checks are conveyed in the fuzzy environment. For the numerical solution of the model, we derive the Forward Euler Method and the fuzzy delayed non-standard finite difference (FDNSFD) method. Analytical studies of the FDNSFD scheme are performed for convergence, non-negativity, boundedness, and consistency analysis of the numerical projection to guarantee that the numerical model is an accurate discretization of the continuous dynamics of FMD transmission over time. In the following simulation study, we show that the FDNSFD method preserves the characteristics of the constant model and still works if relatively large time steps are employed; this is a bonus over the normal finite difference technique. The study shows how valuable it is to adopt fuzzy theory and time delays when simulating the transmission of the epidemic, especially for such diseases as FMD where uncertainty and migration have a defining role in transmission. This approach gives more sound and flexible grounds for analyzing and controlling the outbreak of FMD in various situations. [ABSTRACT FROM AUTHOR]

We consider ridge-type estimation of the multivariate normal distribution's covariance matrix and its inverse, the precision matrix. While several ridge-type covariance and precision matrix estimators have been presented in the literature, their respective inverses are often not considered as precision and covariance matrix estimators even though their estimands are one-to-one related through the matrix inverse. We study which estimator is to be preferred in what case. Hereto we compare the ridge-type covariance matrix estimators and their properties to that of the inverse of the ridge-type precision matrix estimators, and vice versa. The comparison, in which we take all ridge-type estimators along, is limited to a specific case that is illustrative of the difference between the covariance and precision matrix estimators. The comparison addresses the estimators' estimating equation, analytic expression, analytic properties like positive definiteness and penalization limit, mean squared error, consistency, Bayesian formulation, and their loss and potential for marginal and partial correlation screening. [ABSTRACT FROM AUTHOR]

We translated the math novel (A certain ambiguity) during the days of Corona, when the universities were closed, with the hope that math can be brought to the society and reduce the distance between them. First, we will briefly introduce this novel and then we will give a relatively detailed review about it.

Climate change, primarily driven by CO2 emissions from energy and non-energy sectors, necessitates effective mitigation strategies. This study develops a stochastic diffusive model to capture the complex dynamics of CO2 concentration, human population growth, and energy production. The objectives are to enhance the predictive accuracy of existing models by incorporating diffusion effects and stochastic variability, offering insights for sustainable environmental policies. A novel numerical scheme, an extension of the Euler-Maruyama algorithm, is proposed to solve stochastic time-dependent partial differential equations governing the model. The scheme's consistency and stability are rigorously analyzed in the mean square sense. Findings reveal that increasing emission rate coefficients in energy and non-energy sectors exacerbates CO2 levels, emphasizing the need for stringent controls. The proposed scheme demonstrates superior accuracy to the non-standard finite difference method, establishing its efficacy in modeling complex environmental processes. This research contributes a robust computational tool to improve existing predictive models, aiding decision-making for long-term ecological sustainability. By addressing uncertainties in the environmental process, the work advances the understanding of interactions between population growth, energy production, and CO2 emissions, offering a significant improvement over the traditional modeling approach. The novelty lies in integrating stochastic dynamics with diffusion to better inform CO2reduction strategies. Doi: 10.28991/ESJ-2025-09-01-012 Full Text: PDF

This paper will provide information on the impact of AI in daily life and work-related activities.Today, AI functionalities could nowadays transform businesses, playing a critical role in enhancing and improving decisions. From virtual assistants to automation tools, AI covers a great amount of information, which could impact the core. In this paper, the productivity and sense of failure of AI will be paper. The productivity of AI, such as, varies by tasks and industry. AI could excel in repetitive and high-precision tasks. On the other hand, humans outperform AI in tasks requiring creativity and emotional intelligence. This qualitative study will show the perception of integrating AI into workflows and asking questions about value added. To evaluate the impact of artificial intelligence (AI) on business operations, an online survey was conducted to examine perceptions of AI's efficiency, adaptability, and fault tolerance.The analysis revealed generational differences in acceptance and trust towards AI. Younger respondents, particularly those under 25, were found to have greater tolerance for AI errors and a greater willingness to integrate AI into workflows. This is likely to reflect their familiarity with technology. In contrast, older respondents exhibited lower levels of trust and acceptance, particularly in contexts requiring precision, such as financial transactions. The results suggest that while AI is perceived as highly effective in repetitive and data-intensive tasks, its limitations in adaptability and emotional intelligence remain a concern. The findings emohasize the need for reskilling initiatives to facilitate workforce transitions and the development of ethical guidelines to address trust and reliability issues.